Biomolecular Engineering, Bioengineering, Biochemicals, Biofuels, and Food
State and specific growth estimation in heterologous protein production by Pichia pastoris
Article first published online: 22 NOV 2011
DOI: 10.1002/aic.12810
Copyright © 2011 American Institute of Chemical Engineers (AIChE)
Additional Information
How to Cite
Barrigón, J. M., Ramon, R., Rocha, I., Valero, F., Ferreira, E. C. and Montesinos, J. L. (2012), State and specific growth estimation in heterologous protein production by Pichia pastoris. AIChE J., 58: 2966–2979. doi: 10.1002/aic.12810
Publication History
- Issue published online: 10 SEP 2012
- Article first published online: 22 NOV 2011
- Accepted manuscript online: 31 OCT 2011 10:35AM EST
- Manuscript Revised: 29 SEP 2011
- Manuscript Received: 12 NOV 2010
Funded by
- Spanish programme of Chemical Processes Technologies. Grant Numbers: CTQ2007-60347, CTQ2010-15131
- Science and Innovation Ministry. Grant Number: HP2007-0045
- Reference Network in Biotechnology (XRB) from the DURSI (Generalitat de Catalunya). Grant Number: 2009-SGR-00281
- “Luso-Spanish Integrated Actions”. Grant Number: Action 100/08
- Abstract
- Article
- References
- Cited By
Keywords:
- state estimation;
- observers;
- recursive least squares;
- heterologous protein production;
- Pichia pastoris
Abstract
Estimation of biomass, substrate, and specific growth rate (μ) by two nonlinear observers (nonlinear observer-based estimator—NLOBE, asymptotic observer with second-order dynamics tuning—AO-SODE) and a linear estimator (recursive least squares with variable forgetting factor—RLS-VFF) is presented. Heterologous protein production in Pichia pastoris PAOX1 (Mut+) and PFLD1-based systems is closely related to μ and has been addressed due to its high relevance in modern biotechnology and bioprocess engineering. μ was estimated by online gas analyses or substrate measurements, biomass, and substrate considering yield coefficients and mass balances. In simulation studies, NLOBE showed high sensitivity to tuning and initialization variables. Validation experiments demonstrated AO-SODE performs better than the RLS-VFF for moderate to rapid changes of μ and model parameters being known. If low changes on μ are presented, for instance, in substrate regulation, RLS-VFF comes up as the best option, because of its reduced requirements. © 2011 American Institute of Chemical Engineers AIChE J, 58: 2966–2979, 2012

1547-5905/asset/AIC_left.gif?v=1&s=43a3d567c64d3d5d712c0af6c2cacb1e1bcc1a2b)
1547-5905/asset/AIC_right.gif?v=1&s=518efadeedca9ceeef271499f690fdebd2ed9164)
